Probabilistic neural network playing and learning Tic-Tac-Toe
نویسندگان
چکیده
A probabilistic neural network is applied as a tool to approximate the statistical evaluation function for a simple version of the game Tic-Tac-Toe. We solve the problem by a sequential estimation of the underlying discrete distribution mixture of product components.
منابع مشابه
Playing Tic-Tac-Toe Using Genetic Neural Network with Double Transfer Functions
Computational intelligence is a powerful tool for game development. In this paper, an algorithm of playing the game Tic-Tac-Toe with computational intelligence is developed. This algorithm is learned by a Neural Network with Double Transfer functions (NNDTF), which is trained by genetic algorithm (GA). In the NNDTF, the neuron has two transfer functions and exhibits a node-to-node relationship ...
متن کاملCoevolving Probabilistic Game Playing Agents using Particle Swarm Optimization Algorithm
Coevolutionary techniques in combination with particle swarm optimization algorithms and neural networks have shown to be very successful in finding strong game playing agents for a number of deterministic games. This paper investigates the applicability of a PSO coevolutionary approach to probabilistic games. For the purposes of this paper, a probabilistic variation of the tic-tac-toe game is ...
متن کاملAn evolutionary tic-tac-toe player
In this paper, artificial neural networks are used as function evaluators in order to evolve game playing strategies for the game of tic-tac-toe. The best evolved player is tested against an online perfect tic tac toe player, and also against a nearly perfect player which allows 10% random moves and finally against five selected human players. Those players are with different playing abilities....
متن کاملCultural Evolution for Sequential Decision Tasks: Evolving Tic-Tac-Toe Players in Multi-agent Systems
Sequential decision tasks represent a difficult class of problem where perfect solutions are often not available in advance. This paper presents a set of experiments involving populations of agents that evolve to play games of tic–tac–toe. The focus of the paper is to propose that cultural learning, i.e. the passing of information from one generation to the next by non–genetic means, is a bette...
متن کاملLearning to Play Draughts using Temporal Difference Learning with Neural Networks and Databases
This paper describes several aspects of using temporal difference learning (TD) and neural networks to learn game evaluation functions, and the benefits of using databases. Experiments in tic-tac-toe and international draughts have been done to measure the effectiveness of using databases. The experiment of Tic-TacToe showed that training from database games resulted in better play than learnin...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Pattern Recognition Letters
دوره 26 شماره
صفحات -
تاریخ انتشار 2005